Abstract

Assessing and managing extreme risk have to be carried out differently compared with frequent event risk. Especially dependencies among risks are important to be incorporated here. Additionally, dynamics that may alter risk in the future are important to be included in modeling approaches so that strategies to reduce risk are sustainable in the long run. However, little is known about changing risks under dynamic conditions and corresponding advantages and limits of options to decrease or hedge risks. We see this knowledge gap as our starting point to lay out an approach how to model dependencies with the use of copulas and how to manage and prevent increases in risk because of dynamic changes over time. The uniqueness of these approaches is that changes in anticipated losses over different spatial scales (or risks) compared with the current situation are separated into different risk layer, and these different risk layers can be expressed simultaneously with loss distributions. Because risk-reduction and risk-transfer measures are suitable for different risk layers, this distinction can serve in determining the most appropriate risk management measures over different scales. We apply our method to flood risk in Hungary, specifically within the Tisza region. The approach may be particularly useful if dissimilar changes in risk at the local level can be expected, for example, an increase in low-probability events in one region and an increase in the frequency of small magnitude events in a neighboring region.